Summary
Seat-based SaaS pricing helped power the software boom for years. But AI, automation, and changing customer behavior are putting pressure on the model. In this episode, Michael and Avy examine the move toward usage-based and hybrid pricing, the importance of choosing the right metric, and why simplicity may matter more than ever.
Key takeaways
- Seat-based pricing is evolving, not necessarily disappearing.
- AI and automation can reduce the number of users customers need.
- Usage-based pricing only works when the metric reflects real customer value.
- Poorly designed metrics can encourage customers to limit or delay usage.
- Hybrid models can balance flexibility, value, and revenue stability.
- Simple pricing is easier for customers and sales teams to understand.
Why SaaS companies are moving beyond seats
For much of the software industry, charging by the user was a reliable growth model. Customers paid a recurring fee for each employee with access to a platform. As companies grew, software revenue grew with them.
That relationship is now under pressure. AI can automate work that once required several employees, including coding, reporting, administration, and routine analysis. If a customer needs fewer developers, HR specialists, or office users, they may also need fewer software seats.
The same companies that helped popularize subscription pricing are now reconsidering it. Their customers still want predictable costs, but they also expect pricing to reflect the value they receive. A fixed charge for every user can feel disconnected when an AI agent performs much of the work.
For pricing leaders, this is not simply a packaging decision. It is a need to understand how the product creates value today and how that value may change over time. That is where a customized pricing approach, supported by AI-enabled analysis and hands-on expertise, becomes useful.
Usage-based pricing sounds simple, but the metric matters
Moving from seats to usage can look like an obvious answer. However, “usage” is not a pricing strategy by itself. The critical question is: Which usage metric expands as the customer gets more value?
Some activities naturally grow with demand. Others do not. Consider a simple consumer example:
- A two-for-one chocolate promotion may lead someone to consume more.
- A two-for-one offer on laundry detergent may only encourage a bulk purchase. The extra product sits in a cupboard until it is needed.
Software metrics have the same issue. A platform might charge based on the number of performance reviews completed, expense reports filed, or automated tasks run. But does higher usage mean the customer is receiving more value, or will the metric encourage them to reduce activity?
A good metric should do three things:
- Connect clearly to an outcome the customer values.
- Grow naturally as the customer gets more benefit from the product.
- Be difficult to avoid, delay, or manipulate.
Revenue Management Labs often sees this as one of the most important parts of pricing design. Data can help identify patterns quickly, but it still takes pricing judgment and customer understanding to determine whether a metric will work in the real world.
The risk of encouraging the wrong behavior
Pricing metrics do not just measure behavior. They influence it.
Expense management platforms offer a useful example. If customers pay a fee for every expense report, some may delay submitting expenses and combine several months into one report. The customer saves money, but the software company has unintentionally encouraged less frequent usage.
The same problem could arise in an HR platform. If customers are charged for every performance review, they may conduct reviews less often, limit the feature to certain employee groups, or avoid using the tool for lower-priority teams.
This is why pricing teams need to test the likely “game” of the system. Ask what a rational customer would do to reduce their bill. Then consider whether that behavior reduces product adoption, customer outcomes, or long-term revenue.
Hybrid models may offer a better path
The debate is often framed as seats versus usage, but companies do not need to choose one extreme. A hybrid model can combine elements such as:
| Pricing element | What it can provide |
|---|---|
| Fixed fee | Predictability and access to the platform |
| Per-seat charge | A link to the size of the customer’s organization |
| Usage component | Alignment with activity or value delivered |
| Outcome-based component | A closer connection to business results |
The right combination depends on the product, customer segment, data quality, and buying process. A startup may need a lower entry point and more variable pricing. A large enterprise may value predictable spend, governance, and a clear cap on usage charges.
Segmentation should come first. Once a company understands how different customers use the product and what they value, it can decide which pricing structure fits each segment. The goal is not to offer every possible option. It is to offer the right options for the right customers.
Keep the model simple enough to sell
There is a temptation to add more metrics in an effort to capture every form of value. That usually creates confusion. Customers struggle to predict their bills, and sales teams struggle to explain the offer.
A pricing model only works when the commercial organization can use it confidently. Salespeople need to understand why the model exists, which customer it fits, and how to communicate the value. If they cannot explain it clearly, adoption will suffer no matter how strong the underlying analysis is.
This is where implementation matters. Pricing strategy should include enablement, testing, and feedback from the field. Revenue Management Labs’ approach combines custom models with practical execution support so recommendations can hold up in customer conversations, not just in a presentation.
Seat-based SaaS is changing, not dead
The idea that per-seat pricing is finished is probably too extreme. For many products, seats remain a clear and useful proxy for access and value. But the model cannot be treated as automatic or permanent.
SaaS companies need to revisit how customers use their products, how AI changes that usage, and which commercial metric will support long-term growth. A rushed move from seats to usage can create as many problems as it solves.
The stronger approach is measured: study customer behavior, test expandability, choose a small number of understandable metrics, and consider hybrid structures where they make sense. Consistency and simplicity will matter as much as innovation.
The future of SaaS pricing is unlikely to be one universal model. It will be a set of customized approaches built around customer value, product behavior, and the realities of execution.
